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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2023

Genomes to Structure and Function Workshop Report 2022

The goal of the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Program is to achieve a predictive understanding of complex biological, earth, and environmental systems with the aim of advancing the nation’s energy and infrastructure security. (https://www.energy.gov/science/ ber/biological-and-environmental-research). To pursue this goal, collaborations among experts in diverse research areas that lead to multidisciplinary projects are indispensable. The roles of DOE’s User Facilities, which offer unique and powerful resources for such research projects, are evolving, and expectations for the facilities are increasing. To respond to Users’ needs, the Joint Genome Institute (JGI) and Environmental Molecular Sciences Laboratory (EMSL) initiated the Facilities Integrating Collaborations for User Science (FICUS) program in 2014. This collaboration has grown into a popular and successful program, advancing more than 100 multidisciplinary projects to date. Similarly, the new interFacility collaborations among the JGI, EMSL, and User resources for BER structural biology and imaging at the Basic Energy Science (BES) Program’s synchrotron and neutron facilities are becoming essential for cutting-edge transdisciplinary science. To further explore the need for the BER research community to combine genomic, functional, and structural approaches to advance their research, an organizing committee was formed to develop and jointly host a 3-part workshop. The committee’s members represented seven DOE National Laboratory User Facilities (Appendix 1 lists the members). The “Genomes to Structure and Function” virtual workshop (see Appendices 2–5) was composed of three sessions. The first session, titled “Molecular Structures” (October 27– 28, 2021), highlighted diverse integrative experimental and computational approaches correlating structural data with sequencing and functional information, as well as predicting protein structures to model complex biological systems. The second session, “Intracellular Organization, and Material Synthesis and Decomposition” (December 15–16, 2021), covered imaging methods for observing, quantifying, and manipulating biosystems. The third session, “Imaging the Rhizosphere and Cellular Organization” (January 26–27, 2022) emphasized advanced and non-invasive imaging techniques applied to plant root-microbe-soil interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Can Li: A Career in Catalysis

Prof. Can Li is distinguished for his seminal achievements in fundamental and applied researches in catalysis, especially in advancing the characterization of catalysts and catalytic reactions related to solar energy conversion and fine chemical synthesis. The scope of his research is wide ranging, and he is leading some of the fields. This account highlights his major scientific achievements in advancing the fundamental sciences of characterizing catalysts and understanding the mechanisms of catalytic reactions by developing in situ spectroscopic techniques (e.g., infrared (IR), ultraviolet (UV), Raman, space- and time-resolved spectroscopies and photoelectric imaging), and applying the obtained knowledge in the rational design and synthesis of catalysts for practical applications in photocatalytic, electrocatalytic and photoelectrocatalytic water splitting and CO 2 reduction, chiral synthesis in nanoreactors and ultradeep desulfurization of fuels, and fine chemical synthesis. In particular, his demonstration of the kiloton scale solar fuel production project will be introduced as a successful model for converting fundamental science into practical and impactful applications to convert CO 2 and water into solar fuels. This account also highlights his services to the catalysis communities and international collaborations for promoting catalysis science worldwide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Comparison of Results from Recent NNSA and CEA Measurements of the 239 Pu(n, f) Prompt Fission Neutron Spectrum

The National Nuclear Security Administration (NNSA)/DP French Alternative Energies and Atomic Energy Commission (CEA)/DAM agreement on cooperation on fundamental science is a U.S.-French collaborative effort to combine intellectual and experimental resources and further the relevant nuclear science. Recently, both the NNSA and CEA experimental teams performed high-statistics measurements of the 239 Pu(n, f) prompt fission neutron spectrum (PFNS) at the Los Alamos Neutron Science Center, both of which were recently published in the journal Physical Review C. These separate measurements used the same experimental area and a common neutron detector array, but differ in many aspects, including background assessments, data acquisition systems and philosophies, fission detectors, and PFNS extraction techniques. Hence, some aspects of the experimental methods and associated uncertainties are highly correlated while others are independent. The results from both measurements broke new ground for PFNS measurements given their higher accuracy and more detailed study of corrections necessary for the measured quantity compared to existing literature measurements, and both will significantly impact PFNS nuclear data evaluations for the foreseeable future. Here, the focus of this work is to document a comparison of the results from these distinct measurements in terms of the acquired data, the PFNS results, and the measured average PFNS energies. While systematic differences between the PFNS results are present on the 1–3% level, the acquired data relative to each respective measurement at low incident neutron energies are in remarkable agreement, as are the conclusions regarding the magnitude and position of features in the PFNS relating to second-chance fission, third-chance fission, and pre-equilibrium neutron emission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

CAMAS 2025: Continuing to Advance Arctic Marine Science

The Consortium for the Advancement of Marine Arctic Science (CAMAS) held its second annual Workshop and Early-Career School in Seattle, WA, on April 15-18, 2025. The workshop attracted 74 participants, including a dozen scientists from Europe (8) and Asia (4). The goal of CAMAS is to facilitate and enhance international collaboration on marine Arctic science, in order to advance the understanding and model representation of key marine Arctic processes that contribute to the rapid changes in the Arctic Earth system. These rapid changes have profound impacts on operations in the Arctic, including those associated with the national and energy security of the United States. The Early-Career School started the event on Tuesday April 15. Thirty-three early-career scientists (postdocs and students) gathered for lectures and discussions on topics like high-resolution Arctic Ocean and sea ice modeling; biogeochemistry of the Arctic; Machine Learning for Arctic Earth system modeling; and an Arctic perspective on geo-engineering.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The fortedata R package: open-science datasets from a manipulative experiment testing forest resilience

The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. Package data consist of measurements of carbon pools and fluxes and ancillary measurements to help analyze and interpret carbon cycling over time. Currently the package includes data and metadata from the first three FoRTE field seasons, serves as a central, updatable resource for the FoRTE project team, and is intended as a resource for external users over the course of the experiment and in perpetuity. Further, it supports all associated FoRTE publications, analyses, and modeling efforts. This increases efficiency, consistency, compatibility, and productivity while minimizing duplicated effort and error propagation that can arise as a function of a large, distributed and collaborative effort. More broadly, fortedata represents an innovative, collaborative way of approaching science that unites and expedites the delivery of complementary datasets to the broader scientific community, increasing transparency and reproducibility of taxpayer-funded science. The fortedata package is available via GitHub: https://github.com/FoRTExperiment/fortedata (last access: 19 February 2021), and detailed documentation on the access, used, and applications of fortedata are available at https://fortexperiment.github.io/fortedata/ (last access: 19 February 2021). The first public release, version 1.0.1 is also archived at https://doi.org/10.5281/zenodo.4399601 (Atkins et al., 2020b). All data products are also available outside of the package as .csv files: https://doi.org/10.6084/m9.figshare.13499148.v1 (Atkins et al., 2020c).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Overcoming the Challenges to Enhancing Experimental Plant Biology With Computational Modeling

The study of complex biological systems necessitates computational modeling approaches that are currently underutilized in plant biology. Many plant biologists have trouble identifying or adopting modeling methods to their research, particularly mechanistic mathematical modeling. Here we address challenges that limit the use of computational modeling methods, particularly mechanistic mathematical modeling. We divide computational modeling techniques into either pattern models (e.g., bioinformatics, machine learning, or morphology) or mechanistic mathematical models (e.g., biochemical reactions, biophysics, or population models), which both contribute to plant biology research at different scales to answer different research questions. We present arguments and recommendations for the increased adoption of modeling by plant biologists interested in incorporating more modeling into their research programs. As some researchers find math and quantitative methods to be an obstacle to modeling, we provide suggestions for easy-to-use tools for non-specialists and for collaboration with specialists. This may especially be the case for mechanistic mathematical modeling, and we spend some extra time discussing this. Through a more thorough appreciation and awareness of the power of different kinds of modeling in plant biology, we hope to facilitate interdisciplinary, transformative research.

58 GEOSCIENCES↗
DOE OSTI2020

Assessing Single-Source Reproducibility of Human Head Hair Peptide Profiling from Different Regions of the Scalp

Neither microscopical hair comparisons nor mitochondrial DNA sequencing alone, or together, constitutes a basis for personal identification. Due to these limitations, a complementary technique to compare questioned and known hair shafts was investigated. Recently, scientists from Lawrence Livermore National Laboratory's Forensic Science Center and other collaborators developed a peptide profiling technique, which can infer non-synonymous single nucleotide polymorphisms (SNPs) preserved in hair shaft proteins as single amino acid polymorphisms (SAPs). In this study, peptide profiling was evaluated to determine if it can meet forensic expectations when samples are in limited quantities with the possibility that hair samples collected from different areas of a single donor’s scalp (i.e., single source) might not exhibit the same SAP profile. The average dissimilarity, percent differences in SAP profiles within each source, ranged from 0% difference to 29%. This pilot study suggests that more work is needed before peptide profiling of hair can be considered for forensic comparisons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Threat Reduction Research Networks: Fostering Sustainable Collaborations Through Trainings for Genomics for Biosurveillance

Scientific research communities can be represented as heterogeneous or multidimensional networks encompassing multiple types of entities and relationships. These networks might include researchers, institutions, meetings, and publications, connected by relationships like authorship, employment, and attendance. We describe a method for efficiently and flexibly capturing, storing, and extracting information from multidimensional scientific networks using a graph database. The database structure is based on an ontology that captures allowable types of entities and relationships. This allows us to construct a variety of projections of the underlying multidimensional graph through database queries to answer specific research questions. We demonstrate this process through a study of the U.S. Biological Threat Reduction Program (BTRP), which seeks to develop Threat Reduction Networks to build and strengthen a sustainable international community of biosecurity, biosafety, and biosurveillance experts to address shared biological threat reduction challenges. Networks like these create connectional intelligence among researchers and institutions around the world, and are central to the concept of cooperative threat reduction. Our analysis focuses on a series of seven BTRP genome sequencing training workshops, showing how they created a growing network of participants and countries over time, which is also reflected in coauthorship relationships among attendees. By capturing concept and relationship hierarchies, our ontology-based approach allows us to pose general or specific questions about networks within the same framework. This approach can be applied to other research communities or multidimensional social networks to capture, analyze, and visualize different types of interactions and how they change over time.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

CUPID: The Next-Generation Neutrinoless Double Beta Decay Experiment

We report CUPID is a next-generation tonne-scale bolometric neutrinoless double beta decay experiment that will probe the Majorana nature of neutrinos and discover lepton number violation in case of observation of this singular process. CUPID will be built on experience, expertise and lessons learned in CUORE and will be installed in the current CUORE infra-structure in the Gran Sasso underground laboratory. The CUPID detector technology, successfully tested in the CUPID-Mo experiment, is based on scintillating bolometers of Li 2 MoO 4 enriched in the isotope of interest 100 Mo. In order to achieve its ambitious science goals, the CUPID collaboration aims to reduce the backgrounds in the region of interest by a factor 100 with respect to CUORE. This performance will be achieved by introducing the high efficient α/β discrimination demonstrated by the CUPID-0 and CUPID-Mo experiments, and using a high transition energy double beta decay nucleus such as 100 Mo to minimize the impact of the gamma background. CUPID will consist of about 1500 hybrid heat-light detectors for a total isotope mass of 250 kg. The CUPID scientific reach is supported by a detailed and safe background model based on CUORE, CUPID-Mo and CUPID-0 results. The required performances have already been demonstrated and will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Residential Façade Upgrades: Market Assessment and Recommendations

In support of DOE’s move toward transformational whole-building upgrades and enclosure solutions, the Pacific Northwest National Laboratory (PNNL) and National Renewable Energy Laboratory (NREL) are partnering and collaborating with leading building science researchers and home-performance entities to identify and characterize technical and economic barriers to façade retrofits in an effort to identify market-viable façade solutions and opportunities for an actionable plan to transform the market. The project includes partnerships with Building Science Corporation (BSC) and a combination of strategic implementation partners with home-performance and retrofit expertise and industry contacts. The project will include expert advisory and review consultation from Lawrence Berkeley National Laboratory’s (LBNL’s) Residential Windows & Attachments team and Oak Ridge National Laboratory’s Building Envelope team. The project consists of three parts: 1. a market analysis that captures the current state of the façade retrofit market and includes housing characteristics and retrofit costs, façade retrofit approaches and materials, contractor business models and workforce requirements to support advanced façade approaches; 2. an economic analysis focused on the viability of advanced façade retrofit approaches and materials; and 3. field demonstration of façade retrofits that include enhanced insulation/air-sealing and window technologies in multiple climate zones. This report represents the market analysis, as outlined in item 1 above. The goal of this analysis is to provide a techno-economic study that supports comprehensive retrofits of residential enclosures that include traditional approaches, and integrated wall assemblies and windows that result in durable, energy efficient, and marketable strategies. This study will provide a better knowledge base regarding the viable market for façade retrofit strategies, identify the barriers to uptake, analyze economic opportunities, and develop documentation specifically aimed to overcome technical and market barriers associated with installation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

OLCF’s Advanced Computing Ecosystem (ACE): FY24 Efforts for the DOE Integrated Research Infrastructure (IRI) Program

This report highlights significant strides made by Oak Ridge National Laboratory’s Oak Ridge Leadership Computing Facility (OLCF) in advancing computational research and infrastructure. Through the Advanced Computing Ecosystem (ACE) strategic initiative, OLCF has been successfully integrated with Doe’s Integrated Research Infrastructure (IRI) program, establishing itself as a critical framework for enhancing scientific computing capabilities across various domains. This report outlines the activities, accomplishments, and future directions of ACE, emphasizing its role in developing cutting-edge technologies, supporting science pilots, and fostering collaborations that drive scientific innovation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Comparison of GPU-Accelerated Multiphase CFD Solvers on the Polaris Supercomputer: Part 1

This report is in support of the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program sponsored by the U.S. Department of Energy (USDOE). With INCITE-level resources, one project, titled BubblyFlow, was granted computational resources for the 2025 calendar year on the Polaris supercomputer at the Argonne Leadership Computing Facility (ALCF). The project aims to conduct simulations to understand the fundamental characteristics of turbulent bubbly flow phenomena in nature. Staff at the ALCF and Argonne’s Computational Science division, along with collaborators at the City College of New York and University of Illinois at Chicago, helped a summer student to assess the accuracy and performance of two high performance computing (HPC) codes. Both codes, ImExLBM and FluTAS, are fundamentally different in their mathematical and numerical modeling. However, both may be used to solve the same physical problem. The collaboration sought to better understand the differences between both codes in terms of accuracy and efficiency. This would ultimately help the BubblyFlow project better utilize resources and establish a knowledge-base of code capabilities in future simulation campaigns. We compare ImExLBM and FluTAS, two high-performance multiphase computational fluid dynamics (CFD) solvers, in terms of physical fidelity, time-to-solution, and parallel efficiency. We validate ImExLBM (Implicit-Explicit Lattice Boltzmann Method) against a canonical benchmark and assess it’s performance relative to FluTAS (Fluid Transport Accelerated Solver), a well-established open-source CFD code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Challenges and Opportunities in Staffing and Knowledge Transfer at Research Reactors

University research reactors have been a cornerstone of nuclear engineering research and education since the first reactor was deployed at North Carolina State University in the 1950s. The population of university reactors grew to a high of almost 80 in 1970 but has dropped to 24 operating today. The US Department of Energy – Office of Nuclear Energy supports the remaining reactors through fuel and infrastructure funding. The Nuclear Science User Facilities (NSUF) collaborated with the National Organization of Test, Research, and Training Reactors (TRTR) to study the needs of the university research reactor community. Staffing and knowledge transfer were identified as critical areas. The panel will discuss challenges and opportunities in these areas including how COVID-19 has affected their facilities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Expanding Collaborative Capacity to Address Climate Resiliency in the Great Lakes Region

U.S. Department of Energy (DOE), Office of Science, Award DE-SC0023215, Expanding Collaborative Capacity to Address Climate Resiliency in the Great Lakes Region, supported capacity and partnership building between researchers at Central Michigan University (CMU) and scientists at DOE laboratories. The work involved identifying potential collaborations both internal to CMU and between CMU researchers and DOE staff, developing collaborative research proposals, and partnering on pilot-scale research projects focused on enhancing resilience of Great Lakes communities, ecosystems, and infrastructure to global change and environmental stressors. DOE funds supported travel, time to develop collaborations, investigate new research pathways, and draft grant proposals, and a loan of DOE equipment to collect pilot data in support of future work. The project achieved its goal of strengthening research collaborations between interdisciplinary researchers at CMU and establishing new collaborations and partnerships between CMU and DOE scientists. These collaborations resulted in 5 pre-applications and 4 full applications for funding to DOE BER Funding Opportunities, a successfully funded DOE BER award (DE-SC0025260), a new pilot project that leveraged DOE resources (AquaBOT) to improve understanding of water quality conditions in Michigan rivers, and two presentations of preliminary results at national scientific conferences. This project’s outcomes will benefit the Great Lakes Region via new lines of collaborative research focused on improving the resilience of Michigan communities, ecosystems, and infrastructure.

58 GEOSCIENCES↗
DOE OSTI2020

Manipulating Quantum Systems: An Assessment of Atomic, Molecular, and Optical Physics in the United States

The AMO2020 decadal report took a forward-looking perspective on how the different elements that constitute AMO science provide a broad interdisciplinary driver for capitalizing on future opportunities in the scientific community. Goals for this project were to produce a report that (1) displays AMO science as a vital field that relates and unifies broad scientific endeavors; (2) discusses how AMO is supplying these and other fields with emerging technologies and fulfilling national needs; (3) identifies new opportunities, compelling scientific questions, and themes that have arisen from recent advances and accomplishments in the AMO field; (4) explains how AMO science meets workforce, educational, and other societal needs; and (5)makes recommendations for a strategy to fully realize the potential at the frontiers of AMO science. The study also compared the trajectory of AMO science in the US in the context of the international community of AMO science, in terms of cooperation, collaboration, and competition. The study resulted in a report composed in a style accessible to the non-scientist reader in order to understand how AMO science will lead the way in these fields and what AMO researchers want to learn in the coming decades and why.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Physical Sciences Vistas Issue 2, 2020

Dedication and collaboration accelerate mission-essential LANSCE isotope production; Rigorous operations result in newly outfitted gloveboxes; Continuous improvements deliver high-value subcrit data; 'Magnet surge’ expands capabilities for higher tesla science.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

DUNE Phase II: scientific opportunities, detector concepts, technological solutions

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a “Module of Opportunity”, aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Science Gateway for the Repeatable Analysis of Machine Learning Predicted Gravity Anomalies

In recent years, deep learning has become an increasingly popular alternative for modeling in geoscience applications due to its scalability and efficiency. However, the interpretability, compute, data volume, and hyperparameter tuning requirements of deep learning models make development and monitoring difficult. Furthermore, model explainability and communicating results obtained by these models to users or domain experts is a challenge, as domain experts in geoscience also need to have a deep understanding of how those models function in order to support their scientific works. Here, we describe a science gateway and machine learning pipeline for predicting gravity anomalies from geophysical data. The gateway, built on open-source technologies, provides a holistic view of the pipeline through interactive visualizations aimed at enabling efficient exploratory data analysis. The repeatability, reproducibility, and monitoring capabilities of this overall system allow us to iterate and analyze at scale. Using this pipeline and gateway, we can repeatedly produce accurate high-resolution gravity anomaly datasets. By describing the underlying technologies, implementation, and results, here we provide a foundation for the broader adoption of science gateways into cross-cutting geoscience and machine learning research projects as a means to improve the scientific discovery and collaboration in the geophysics and computational sciences community.

58 GEOSCIENCES↗